The nature of statistical learning theory
The nature of statistical learning theory
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coding Facial Expressions with Gabor Wavelets
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Estimating intervals of interest during TV viewing for automatic personal preference acquisition
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Discrimination of media moments and media intervals: sticker-based watch-and-comment annotation
Multimedia Tools and Applications
Robust facial expressions recognition using 3D average face and ameliorated adaboost
Proceedings of the 21st ACM international conference on Multimedia
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Recently, there are so many videos available for people to choose to watch. To solve this problem, we propose a tagging system for video content based on facial expression that can be used for recommendations based on video content. Viewer's face captured by a camera is extracted by Elastic Bunch Graph Matching, and the facial expression is recognized by Support Vector Machines. The facial expression is classified into Neutral, Positive, Negative and Rejective. Recognition results are recorded as "facial expression tags" in synchronization with video content. Experimental results achieved an averaged recall rate of 87.61%, and averaged precision rate of 88.03%.